积雪遥感监测产品研究与应用进展

doi:10.6046/zrzyyg.2023065

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摘要

积雪是表征地表冰冻圈的重要因子,也是重要的天气、水文现象的参数。借助遥感技术对积雪形态及变化进行长时序、大范围监测,在全球气候变化研究、水文水资源调查和地质灾害预防等领域有重要作用。经过数十年的发展,国内外积雪遥感监测技术领域取得了很大进展,积雪遥感监测产品种类不断丰富,积雪反演的算法也在不断改进。文章对现有应用比较广泛的积雪产品按照积雪范围产品、积雪覆盖率产品和雪深/雪水当量产品3类进行归纳总结,梳理当前典型积雪范围及覆盖率产品和雪深/雪水当量产品的业务化遥感反演算法。文章指出,随着国内外高时间和空间分辨率传感器的不断出现,在光学和微波新数据源、新技术支持下,研究人员逐渐针对区域特点优化积雪反演算法,使得反演精度不断提高,为未来积雪遥感监测产品的不断改进提供更多支持。

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	孙禧勇
	刘稼丰
	范景辉
	张文凯
	石利娟
	邱玉宝
	朱发容

关键词 ：积雪遥感监测产品, 积雪覆盖, 雪水当量, 积雪反演算法

Abstract：

Snow proves to be both an important factor in characterizing the surface cryosphere and a critical parameter for weather and hydrological phenomena. Employing remote sensing to conduct long-term and large-scale monitoring of snow morphologies and their changes plays a vital role in research into global climate change, investigations into hydrology and water resources, and geological disaster prevention. After decades of development, significant progress has been made in the field of remote sensing-based snow monitoring technology both in China and abroad. Accordingly, the products for remote sensing-based snow monitoring have become increasingly abundant, and the snow-orientated inversion algorithms have been continuously improved. This paper provides a summary of the existing, widely applied products after categorizing them into three types: snow-cover extent (SEC), snow coverage, and snow depth/snow water equivalent (SWE) products. Furthermore, this study organizes the commercialized remote sensing inversion algorithms used in existing, typical SEC and SWE products. The review of advances in the relevant scientific research reveals that, with the constant presence of sensors with high temporal and spatial resolutions in China and abroad and the support of both novel optical and microwave data sources and new technologies, researchers have gradually improved the accuracy of snow-orientated inversion algorithms by optimizing these algorithms based on regional characteristics. This will provide more support for continuously improving remote sensing-based snow monitoring products in the future.

Key words： remote sensing-based snow monitoring product snow cover SWE snow-orientated inversion algorithm

收稿日期: 2023-03-15 出版日期: 2024-09-03

ZTFLH:

TP79

基金资助:国家重点研发计划项目“高亚洲和北极积雪—冰川与地质灾害监测技术及示范应用”(2021YFE0116800)

通讯作者: 范景辉(1978-),男,博士,正高级工程师,主要从事环境遥感研究。Email: fanjinghui@mail.cgs.gov.cn。

作者简介: 孙禧勇(1984-),男,博士研究生,正高级工程师,主要从事自然资源遥感研究。Email: sunxiyong@mail.cgs.gov.cn。

引用本文:

孙禧勇, 刘稼丰, 范景辉, 张文凯, 石利娟, 邱玉宝, 朱发容. 积雪遥感监测产品研究与应用进展[J]. 自然资源遥感, 2024, 36(3): 13-27.
SUN Xiyong, LIU Jiafeng, FAN Jinghui, ZHANG Wenkai, SHI Lijuan, QIU Yubao, ZHU Farong. Advances in research and application of remote sensing-based snow monitoring products. Remote Sensing for Natural Resources, 2024, 36(3): 13-27.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023065 或 https://www.gtzyyg.com/CN/Y2024/V36/I3/13

传感器名称	传感器类型	波长(频率)	空间分辨率/km	观测幅度/km	搭载卫星
TM	光学传感器	0.45~0.52 μm		185	Landsat5 (1984—2011年) 美国
		0.52~0.60 μm
		0.63~0.69 μm	0.03
		0.75~0.90 μm
		1.55~1.75 μm
		2.08~2.35 μm
		10.40~12.50 μm	0.12
ETM+	光学传感器	0.52~0.90 μm	0.015	185	Landsat7 (1999年至今) 美国
		0.45~0.52 μm
		0.525~0.605 μm
		0.63~0.69 μm	0.03
		0.75~0.90 μm
		1.55~1.75 μm
		2.09~2.35 μm
		10.40~12.50 μm	0.06
OLI	光学传感器	0.433~0.453 μm		185	Landsat8 (2013年至今) 美国
		0.450~0.515 μm
		0.525~0.600 μm
		0.630~0.680 μm	0.03
		0.845~0.885 μm
		1.560~1.660 μm
		2.100~2.300 μm
		1.360~1.390 μm
		0.500~0.680 μm	0.015
MODIS	光学传感器	0.620~0.876 μm	0.25	2 330	EOS Terra (1999年至今) 美国/日本/加拿大
		0.459~2.155 μm	0.5
		0.405~0.877 μm	1
		0.890~0.965 μm	1
		3.660~14.385 μm	1
NOAA/AVHRR	光学传感器	0.58~0.68 μm	1.09	2 800	TIROS-N (1979年至今) 美国
		0.725~1.00 μm
		1.58~1.64 μm
		3.55~3.93 μm
		10.30~11.30 μm
		11.50~12.50 μm
MODIS	光学传感器	0.620~0.876 μm	0.25	2 330	EOS Aqua (2001年至今) 美国
		0.459~2.155 μm	0.5
		0.405~0.877 μm	1
		0.890~0.965 μm	1
		3.660~14.385 μm	1
AMSR-E	被动微波传感器	6.925 GHz		1 445	EOS Aqua (2001年至今) 美国
		10.65 GHz	10
		18.7 GHz
		23.8 GHz
		36.5 GHz	5
		89.0 GHz
SMMR	被动微波传感	6.33 GHz 10.69 GHz 18.00 GHz 21.00 GHz 37.00 GHz	96×153 59×91 41×55 30×46 18×27	地平线 \| 地平线	NIMBUS-7
MWRI	被动微波传感器	10.65 GHz 18.70 GHz 23.80 GHz 36.50 GHz 89.00 GHz	85×51 50×30 45×27 30×18 15×9	1 400	FY-3B/3C/3D (2008年至今/2010年至今/2013年至今) 中国
SMM/I	被动微波传感器	19.30 GHz 22.20 V 37.00 GHz 85.50 GHz	70×45 60×40 38×30 16×14	1 394	DMSP-F8/ F11/ F13 (1987—1991年/1991— 2000年/1995—2009年) 美国
SSMIS	被动微波传感器	19.30 GHz 22.20 V 37.00 GHz 85.50 GHz	70×45 60×40 38×30 16×13	1 700	DMSP-F17 (2006—2017年) 美国
SSMIS	被动微波传感器	19.30 GHz 22.20 V 37.00 GHz 85.50 GHz	70×45 60×40 38×30 16×13	1 700	DMSP-F18 (2009年至今) 美国
Sentinel-1A	主动微波传感器	C波段: 5.405 GHz	0.025	>80	Sentinel (2014—2016年) 欧洲太空局
Sentinel-1A			0.1	>250
Sentinel-1B			1	>400
Sentinel-1B			0.025	400

Tab.1 积雪遥感常用传感器

Tab.2 主要的积雪范围产品

Tab.3 主要积雪覆盖率产品

Tab.4 典型的雪深/雪水当量产品

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